---
library_name: transformers
license: apache-2.0
base_model: dandelin/vilt-b32-finetuned-nlvr2
tags:
- image-text-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: '42'
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 42

This model is a fine-tuned version of [dandelin/vilt-b32-finetuned-nlvr2](https://huggingface.co/dandelin/vilt-b32-finetuned-nlvr2) on the nlvr2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9443
- Accuracy: 0.7327
- Dt Accuracy: 0.7327
- Df Accuracy: 0.4959
- Unlearn Overall Accuracy: 0.8978
- Unlearn Time: None

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:|
| 0.3079        | 1.0   | 2700  | 0.5663          | 0.8542   | 0.6449           | 0.6449                   | None |
| 0.2432        | 2.0   | 5400  | 0.6403          | 0.7017   | 0.7676           | 0.7676                   | None |
| 0.1905        | 3.0   | 8100  | 0.7980          | 0.5862   | 0.8458           | 0.8458                   | None |
| 0.1569        | 4.0   | 10800 | 0.8834          | 0.5176   | 0.8863           | 0.8863                   | None |
| 0.1273        | 5.0   | 13500 | 0.9443          | 0.4959   | 0.8978           | 0.8978                   | None |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.21.0